Smart health system using stacking ensemble classification algorithm
2022, vol.14 , no.3, pp. 67-78
Data Mining is a powerful technology and is used to identify useful and understandable patterns by analyzing large sets of data. It gives a detailed view of various disease predictions. It will be more useful especially in pandemic times. During these days, doctors are in the front line and battling with the COVID-19 virus. It will be hard for people to immediately get medical guidance or appointments. Our proposed system, the smart health application will come in handy at these times. The system allows people to get medical guidance for their health issues. Also, the system is fed with symptoms and the disease-related with it which will give high accuracy for disease prediction. Our model aims to use Stacking Ensemble Classification Algorithms to give high accuracy and correct prediction than Naive Bayes, Random Forest, Support Vector Machine, K – Nearest Neighbor, Decision Tree, Logistic Regression for different types of 149 diseases. The GUI is designed which can be used easily to predict the different types of disease accurately.
Classification, Diseases, Ensemble Learning, Machine Learning, Symptoms
Sathya D., Primya T., Vinothini S., Priya J., Jagadeesan D.. Smart health system using stacking ensemble classification algorithm. International Journal on Information Technologies and Security, vol.14 , no.3, 2022, pp. 67-78.